Overview

Dataset statistics

Number of variables28
Number of observations29182
Missing cells93232
Missing cells (%)11.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 MiB
Average record size in memory224.0 B

Variable types

Numeric10
Text10
Categorical6
Unsupported1
DateTime1

Alerts

Company Status (Active/Inactive) has constant value ""Constant
SIC Code is highly overall correlated with 8-Digit SIC CodeHigh correlation
8-Digit SIC Code is highly overall correlated with SIC CodeHigh correlation
Employees (Domestic Ultimate Total) is highly overall correlated with Employees (Global Ultimate Total) and 2 other fieldsHigh correlation
Employees (Global Ultimate Total) is highly overall correlated with Employees (Domestic Ultimate Total) and 2 other fieldsHigh correlation
Sales (Domestic Ultimate Total USD) is highly overall correlated with Employees (Domestic Ultimate Total) and 2 other fieldsHigh correlation
Sales (Global Ultimate Total USD) is highly overall correlated with Employees (Domestic Ultimate Total) and 2 other fieldsHigh correlation
Entity Type is highly overall correlated with Is Domestic Ultimate and 1 other fieldsHigh correlation
Is Domestic Ultimate is highly overall correlated with Entity Type and 1 other fieldsHigh correlation
Is Global Ultimate is highly overall correlated with Entity Type and 1 other fieldsHigh correlation
Entity Type is highly imbalanced (51.6%)Imbalance
Ownership Type is highly imbalanced (91.3%)Imbalance
Year Found has 434 (1.5%) missing valuesMissing
Parent Company has 514 (1.8%) missing valuesMissing
Parent Country has 520 (1.8%) missing valuesMissing
Square Footage has 29182 (100.0%) missing valuesMissing
Employees (Single Site) has 12403 (42.5%) missing valuesMissing
Employees (Global Ultimate Total) has 2774 (9.5%) missing valuesMissing
Import/Export Status has 22569 (77.3%) missing valuesMissing
Fiscal Year End has 22445 (76.9%) missing valuesMissing
Global Ultimate Company has 514 (1.8%) missing valuesMissing
Global Ultimate Country has 523 (1.8%) missing valuesMissing
Domestic Ultimate Company has 1035 (3.5%) missing valuesMissing
Employees (Single Site) is highly skewed (γ1 = 36.26068396)Skewed
Employees (Domestic Ultimate Total) is highly skewed (γ1 = 36.21641929)Skewed
Sales (Domestic Ultimate Total USD) is highly skewed (γ1 = 26.26411238)Skewed
AccountID has unique valuesUnique
Company has unique valuesUnique
Square Footage is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-01-26 06:20:34.888838
Analysis finished2024-01-26 06:20:47.491586
Duration12.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

LATITUDE
Real number (ℝ)

Distinct9305
Distinct (%)32.0%
Missing120
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean1.3206765
Minimum1.2387923
Maximum1.4698001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size228.1 KiB
2024-01-26T14:20:47.554982image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum1.2387923
5-th percentile1.2757357
Q11.2846651
median1.3097007
Q31.3378894
95-th percentile1.427295
Maximum1.4698001
Range0.23100784
Interquartile range (IQR)0.053224379

Descriptive statistics

Standard deviation0.04373966
Coefficient of variation (CV)0.033119132
Kurtosis1.1054646
Mean1.3206765
Median Absolute Deviation (MAD)0.026397746
Skewness1.2406998
Sum38381.501
Variance0.0019131578
MonotonicityNot monotonic
2024-01-26T14:20:47.636459image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.275735681 736
 
2.5%
1.277630733 664
 
2.3%
1.27812791 338
 
1.2%
1.31881487 317
 
1.1%
1.28013747 261
 
0.9%
1.286394381 246
 
0.8%
1.282887374 186
 
0.6%
1.358579001 181
 
0.6%
1.295435698 177
 
0.6%
1.292220758 177
 
0.6%
Other values (9295) 25779
88.3%
ValueCountFrequency (%)
1.238792312 1
< 0.1%
1.240391637 2
< 0.1%
1.24040896 1
< 0.1%
1.240783982 1
< 0.1%
1.240926782 1
< 0.1%
1.241066162 1
< 0.1%
1.241366523 1
< 0.1%
1.241407809 1
< 0.1%
1.241651787 2
< 0.1%
1.241982688 1
< 0.1%
ValueCountFrequency (%)
1.469800148 1
< 0.1%
1.469799738 2
< 0.1%
1.469281638 1
< 0.1%
1.469245574 1
< 0.1%
1.46889153 1
< 0.1%
1.468827737 2
< 0.1%
1.468386933 1
< 0.1%
1.468103855 1
< 0.1%
1.467945082 1
< 0.1%
1.467477028 1
< 0.1%

LONGITUDE
Real number (ℝ)

Distinct9307
Distinct (%)32.0%
Missing120
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean103.84332
Minimum103.61132
Maximum104.00322
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size228.1 KiB
2024-01-26T14:20:47.719574image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum103.61132
5-th percentile103.74457
Q1103.83187
median103.84899
Q3103.86592
95-th percentile103.92567
Maximum104.00322
Range0.39189912
Interquartile range (IQR)0.03404759

Descriptive statistics

Standard deviation0.053757254
Coefficient of variation (CV)0.00051767655
Kurtosis2.1057524
Mean103.84332
Median Absolute Deviation (MAD)0.017008492
Skewness-0.886304
Sum3017894.7
Variance0.0028898424
MonotonicityNot monotonic
2024-01-26T14:20:47.804010image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
103.8457032 736
 
2.5%
103.8475727 664
 
2.3%
103.8478546 338
 
1.2%
103.8925808 317
 
1.1%
103.8493164 261
 
0.9%
103.8489887 246
 
0.8%
103.8508488 186
 
0.6%
103.833601 181
 
0.6%
103.8583748 177
 
0.6%
103.8506126 177
 
0.6%
Other values (9297) 25779
88.3%
ValueCountFrequency (%)
103.611319 4
< 0.1%
103.6193581 1
 
< 0.1%
103.6225954 1
 
< 0.1%
103.6228141 1
 
< 0.1%
103.6229391 1
 
< 0.1%
103.6231306 2
< 0.1%
103.6231334 3
< 0.1%
103.6236092 1
 
< 0.1%
103.6236791 1
 
< 0.1%
103.6238669 1
 
< 0.1%
ValueCountFrequency (%)
104.0032182 2
 
< 0.1%
104.0021063 1
 
< 0.1%
104.000953 1
 
< 0.1%
103.9999304 8
< 0.1%
103.9994268 12
< 0.1%
103.9977782 1
 
< 0.1%
103.9973054 3
 
< 0.1%
103.9971074 1
 
< 0.1%
103.9966959 1
 
< 0.1%
103.9958504 10
< 0.1%

AccountID
Text

UNIQUE 

Distinct29182
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size228.1 KiB
2024-01-26T14:20:47.950457image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length16
Median length15
Mean length14.888904
Min length11

Characters and Unicode

Total characters434488
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29182 ?
Unique (%)100.0%

Sample

1st rowLAKB2BID4559214
2nd rowLAKB2BID7610849
3rd rowLAKB2BID5461679
4th rowLAKB2BID5088529
5th rowLAKB2BID1268831
ValueCountFrequency (%)
lakb2bid4559214 1
 
< 0.1%
lakb2bid4741194 1
 
< 0.1%
lakb2bid5088529 1
 
< 0.1%
lakb2bid1268831 1
 
< 0.1%
lakb2bid2264578 1
 
< 0.1%
lakb2bid1559931 1
 
< 0.1%
lakb2bid679914 1
 
< 0.1%
lakb2bid4688489 1
 
< 0.1%
lakb2bid5108278 1
 
< 0.1%
lakb2bid327378 1
 
< 0.1%
Other values (29172) 29172
> 99.9%
2024-01-26T14:20:48.159870image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 58364
13.4%
2 49619
11.4%
L 29182
 
6.7%
A 29182
 
6.7%
K 29182
 
6.7%
I 29182
 
6.7%
D 29182
 
6.7%
8 20571
 
4.7%
1 20535
 
4.7%
4 20461
 
4.7%
Other values (6) 119028
27.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 230214
53.0%
Uppercase Letter 204274
47.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 49619
21.6%
8 20571
8.9%
1 20535
8.9%
4 20461
8.9%
3 20411
8.9%
6 20407
8.9%
5 20385
8.9%
7 20325
8.8%
9 20285
8.8%
0 17215
 
7.5%
Uppercase Letter
ValueCountFrequency (%)
B 58364
28.6%
L 29182
14.3%
A 29182
14.3%
K 29182
14.3%
I 29182
14.3%
D 29182
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 230214
53.0%
Latin 204274
47.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 49619
21.6%
8 20571
8.9%
1 20535
8.9%
4 20461
8.9%
3 20411
8.9%
6 20407
8.9%
5 20385
8.9%
7 20325
8.8%
9 20285
8.8%
0 17215
 
7.5%
Latin
ValueCountFrequency (%)
B 58364
28.6%
L 29182
14.3%
A 29182
14.3%
K 29182
14.3%
I 29182
14.3%
D 29182
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 434488
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B 58364
13.4%
2 49619
11.4%
L 29182
 
6.7%
A 29182
 
6.7%
K 29182
 
6.7%
I 29182
 
6.7%
D 29182
 
6.7%
8 20571
 
4.7%
1 20535
 
4.7%
4 20461
 
4.7%
Other values (6) 119028
27.4%

Company
Text

UNIQUE 

Distinct29182
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size228.1 KiB
2024-01-26T14:20:48.356267image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length89
Median length67
Mean length29.287198
Min length8

Characters and Unicode

Total characters854659
Distinct characters44
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29182 ?
Unique (%)100.0%

Sample

1st rowFRANK CONSULTING SERVICES PRIVATE LIMITED
2nd rowNEW DESERT ORCHID SHIPPING PTE. LTD.
3rd row2MBAO BIOCELLBANK PTE. LTD.
4th rowNEWBLOOM PTE. LTD.
5th rowASIA GREEN CAPITAL PTE. LTD.
ValueCountFrequency (%)
pte 26565
19.7%
ltd 26400
 
19.6%
singapore 4465
 
3.3%
limited 2277
 
1.7%
asia 2223
 
1.6%
holdings 2091
 
1.6%
private 1256
 
0.9%
international 1217
 
0.9%
investment 1038
 
0.8%
991
 
0.7%
Other values (20215) 66361
49.2%
2024-01-26T14:20:48.750919image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
105702
12.4%
T 90136
 
10.5%
E 83341
 
9.8%
I 53054
 
6.2%
L 51602
 
6.0%
A 48466
 
5.7%
P 45855
 
5.4%
N 45842
 
5.4%
. 43770
 
5.1%
S 41125
 
4.8%
Other values (34) 245766
28.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 693268
81.1%
Space Separator 105702
 
12.4%
Other Punctuation 44946
 
5.3%
Open Punctuation 4043
 
0.5%
Close Punctuation 4041
 
0.5%
Decimal Number 1670
 
0.2%
Dash Punctuation 989
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 90136
13.0%
E 83341
12.0%
I 53054
 
7.7%
L 51602
 
7.4%
A 48466
 
7.0%
P 45855
 
6.6%
N 45842
 
6.6%
S 41125
 
5.9%
D 40939
 
5.9%
O 36349
 
5.2%
Other values (16) 156559
22.6%
Decimal Number
ValueCountFrequency (%)
1 402
24.1%
2 343
20.5%
3 198
11.9%
0 160
 
9.6%
9 119
 
7.1%
8 113
 
6.8%
4 99
 
5.9%
7 84
 
5.0%
5 79
 
4.7%
6 73
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 43770
97.4%
& 1088
 
2.4%
, 67
 
0.1%
/ 21
 
< 0.1%
Space Separator
ValueCountFrequency (%)
105702
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4043
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4041
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 989
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 693268
81.1%
Common 161391
 
18.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 90136
13.0%
E 83341
12.0%
I 53054
 
7.7%
L 51602
 
7.4%
A 48466
 
7.0%
P 45855
 
6.6%
N 45842
 
6.6%
S 41125
 
5.9%
D 40939
 
5.9%
O 36349
 
5.2%
Other values (16) 156559
22.6%
Common
ValueCountFrequency (%)
105702
65.5%
. 43770
27.1%
( 4043
 
2.5%
) 4041
 
2.5%
& 1088
 
0.7%
- 989
 
0.6%
1 402
 
0.2%
2 343
 
0.2%
3 198
 
0.1%
0 160
 
0.1%
Other values (8) 655
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 854659
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
105702
12.4%
T 90136
 
10.5%
E 83341
 
9.8%
I 53054
 
6.2%
L 51602
 
6.0%
A 48466
 
5.7%
P 45855
 
5.4%
N 45842
 
5.4%
. 43770
 
5.1%
S 41125
 
4.8%
Other values (34) 245766
28.8%

SIC Code
Real number (ℝ)

HIGH CORRELATION 

Distinct582
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6169.2712
Minimum132
Maximum9721
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size228.1 KiB
2024-01-26T14:20:48.837575image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum132
5-th percentile2819
Q15084
median6719
Q37311
95-th percentile8742
Maximum9721
Range9589
Interquartile range (IQR)2227

Descriptive statistics

Standard deviation1705.8455
Coefficient of variation (CV)0.27650682
Kurtosis0.40533603
Mean6169.2712
Median Absolute Deviation (MAD)985
Skewness-0.66911754
Sum1.8003167 × 108
Variance2909909
MonotonicityNot monotonic
2024-01-26T14:20:48.915010image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6719 7753
26.6%
8742 1389
 
4.8%
7371 778
 
2.7%
4731 737
 
2.5%
7389 694
 
2.4%
5099 668
 
2.3%
8711 580
 
2.0%
6552 580
 
2.0%
4499 554
 
1.9%
5812 527
 
1.8%
Other values (572) 14922
51.1%
ValueCountFrequency (%)
132 3
 
< 0.1%
161 3
 
< 0.1%
179 2
 
< 0.1%
181 3
 
< 0.1%
191 3
 
< 0.1%
273 4
< 0.1%
711 3
 
< 0.1%
742 6
< 0.1%
751 2
 
< 0.1%
781 8
< 0.1%
ValueCountFrequency (%)
9721 11
< 0.1%
9711 5
 
< 0.1%
9651 3
 
< 0.1%
9641 2
 
< 0.1%
9621 15
0.1%
9311 4
 
< 0.1%
9224 2
 
< 0.1%
9221 3
 
< 0.1%
9211 2
 
< 0.1%
9199 22
0.1%
Distinct580
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size228.1 KiB
2024-01-26T14:20:49.109193image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length103
Median length84
Mean length43.921253
Min length6

Characters and Unicode

Total characters1281710
Distinct characters57
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEmployment Agencies
2nd rowWater Transportation of Freight, Not Elsewhere Classified
3rd rowOffices of Holding Companies, Not Elsewhere Classified
4th rowOffices of Holding Companies, Not Elsewhere Classified
5th rowOffices of Holding Companies, Not Elsewhere Classified
ValueCountFrequency (%)
not 14110
 
8.8%
elsewhere 14110
 
8.8%
classified 14110
 
8.8%
and 10937
 
6.8%
of 10056
 
6.3%
offices 8768
 
5.5%
companies 8319
 
5.2%
holding 8243
 
5.2%
services 6727
 
4.2%
equipment 2087
 
1.3%
Other values (945) 62252
39.0%
2024-01-26T14:20:49.386903image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 143279
 
11.2%
130537
 
10.2%
s 100653
 
7.9%
i 98668
 
7.7%
o 72227
 
5.6%
a 70281
 
5.5%
n 67425
 
5.3%
l 59683
 
4.7%
r 59132
 
4.6%
t 53586
 
4.2%
Other values (47) 426239
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 991295
77.3%
Uppercase Letter 138779
 
10.8%
Space Separator 130537
 
10.2%
Other Punctuation 19867
 
1.6%
Dash Punctuation 822
 
0.1%
Open Punctuation 205
 
< 0.1%
Close Punctuation 205
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 143279
14.5%
s 100653
10.2%
i 98668
10.0%
o 72227
 
7.3%
a 70281
 
7.1%
n 67425
 
6.8%
l 59683
 
6.0%
r 59132
 
6.0%
t 53586
 
5.4%
d 44652
 
4.5%
Other values (16) 221709
22.4%
Uppercase Letter
ValueCountFrequency (%)
C 31447
22.7%
E 21352
15.4%
N 14662
10.6%
S 12850
9.3%
O 9625
 
6.9%
H 9314
 
6.7%
P 6548
 
4.7%
M 5558
 
4.0%
B 3654
 
2.6%
A 3612
 
2.6%
Other values (14) 20157
14.5%
Other Punctuation
ValueCountFrequency (%)
, 19510
98.2%
' 345
 
1.7%
; 12
 
0.1%
Space Separator
ValueCountFrequency (%)
130537
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 822
100.0%
Open Punctuation
ValueCountFrequency (%)
( 205
100.0%
Close Punctuation
ValueCountFrequency (%)
) 205
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1130074
88.2%
Common 151636
 
11.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 143279
 
12.7%
s 100653
 
8.9%
i 98668
 
8.7%
o 72227
 
6.4%
a 70281
 
6.2%
n 67425
 
6.0%
l 59683
 
5.3%
r 59132
 
5.2%
t 53586
 
4.7%
d 44652
 
4.0%
Other values (40) 360488
31.9%
Common
ValueCountFrequency (%)
130537
86.1%
, 19510
 
12.9%
- 822
 
0.5%
' 345
 
0.2%
( 205
 
0.1%
) 205
 
0.1%
; 12
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1281710
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 143279
 
11.2%
130537
 
10.2%
s 100653
 
7.9%
i 98668
 
7.7%
o 72227
 
5.6%
a 70281
 
5.5%
n 67425
 
5.3%
l 59683
 
4.7%
r 59132
 
4.6%
t 53586
 
4.2%
Other values (47) 426239
33.3%

8-Digit SIC Code
Real number (ℝ)

HIGH CORRELATION 

Distinct2255
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61690924
Minimum1320000
Maximum97219905
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size228.1 KiB
2024-01-26T14:20:49.476337image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum1320000
5-th percentile28190000
Q150840000
median67190000
Q373110000
95-th percentile87420000
Maximum97219905
Range95899905
Interquartile range (IQR)22270000

Descriptive statistics

Standard deviation17057775
Coefficient of variation (CV)0.27650381
Kurtosis0.40538356
Mean61690924
Median Absolute Deviation (MAD)9849800
Skewness-0.66926906
Sum1.8002645 × 1012
Variance2.909677 × 1014
MonotonicityNot monotonic
2024-01-26T14:20:49.555833image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
67190000 6461
 
22.1%
67199901 1261
 
4.3%
87420000 1160
 
4.0%
50990000 622
 
2.1%
65520000 568
 
1.9%
67120000 490
 
1.7%
73890000 475
 
1.6%
73710000 466
 
1.6%
47310000 445
 
1.5%
87110000 438
 
1.5%
Other values (2245) 16796
57.6%
ValueCountFrequency (%)
1320000 3
< 0.1%
1610000 3
< 0.1%
1790000 2
 
< 0.1%
1810000 3
< 0.1%
1910000 3
< 0.1%
2730000 4
< 0.1%
7119906 3
< 0.1%
7420000 6
< 0.1%
7510000 2
 
< 0.1%
7810000 5
< 0.1%
ValueCountFrequency (%)
97219905 1
 
< 0.1%
97219903 1
 
< 0.1%
97210000 9
< 0.1%
97119907 1
 
< 0.1%
97110000 4
< 0.1%
96519903 1
 
< 0.1%
96510000 2
 
< 0.1%
96419901 2
 
< 0.1%
96219904 1
 
< 0.1%
96210300 3
 
< 0.1%
Distinct2191
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size228.1 KiB
2024-01-26T14:20:49.755964image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length63
Median length57
Mean length26.332499
Min length3

Characters and Unicode

Total characters768435
Distinct characters63
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique953 ?
Unique (%)3.3%

Sample

1st rowEmployment agencies
2nd rowWater transportation of freight
3rd rowHolding companies, nec
4th rowHolding companies, nec
5th rowHolding companies, nec
ValueCountFrequency (%)
nec 11864
 
12.2%
companies 8316
 
8.6%
holding 8244
 
8.5%
and 6461
 
6.6%
services 5135
 
5.3%
management 1827
 
1.9%
investment 1537
 
1.6%
consulting 1516
 
1.6%
equipment 1487
 
1.5%
computer 1478
 
1.5%
Other values (2001) 49308
50.7%
2024-01-26T14:20:50.057628image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 84085
 
10.9%
n 73909
 
9.6%
67991
 
8.8%
i 54678
 
7.1%
s 52695
 
6.9%
a 48945
 
6.4%
c 44520
 
5.8%
o 43552
 
5.7%
t 37860
 
4.9%
r 37256
 
4.8%
Other values (53) 222944
29.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 653828
85.1%
Space Separator 67991
 
8.8%
Uppercase Letter 29378
 
3.8%
Other Punctuation 16773
 
2.2%
Dash Punctuation 317
 
< 0.1%
Open Punctuation 71
 
< 0.1%
Close Punctuation 71
 
< 0.1%
Decimal Number 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 84085
12.9%
n 73909
11.3%
i 54678
 
8.4%
s 52695
 
8.1%
a 48945
 
7.5%
c 44520
 
6.8%
o 43552
 
6.7%
t 37860
 
5.8%
r 37256
 
5.7%
l 26914
 
4.1%
Other values (16) 149414
22.9%
Uppercase Letter
ValueCountFrequency (%)
H 6985
23.8%
C 3317
11.3%
M 2813
9.6%
S 2298
 
7.8%
I 2266
 
7.7%
E 1893
 
6.4%
B 1868
 
6.4%
F 1210
 
4.1%
P 1072
 
3.6%
D 1039
 
3.5%
Other values (14) 4617
15.7%
Other Punctuation
ValueCountFrequency (%)
, 16428
97.9%
' 138
 
0.8%
: 128
 
0.8%
. 54
 
0.3%
/ 15
 
0.1%
; 6
 
< 0.1%
& 4
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 5
83.3%
1 1
 
16.7%
Space Separator
ValueCountFrequency (%)
67991
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 317
100.0%
Open Punctuation
ValueCountFrequency (%)
( 71
100.0%
Close Punctuation
ValueCountFrequency (%)
) 71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 683206
88.9%
Common 85229
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 84085
12.3%
n 73909
10.8%
i 54678
 
8.0%
s 52695
 
7.7%
a 48945
 
7.2%
c 44520
 
6.5%
o 43552
 
6.4%
t 37860
 
5.5%
r 37256
 
5.5%
l 26914
 
3.9%
Other values (40) 178792
26.2%
Common
ValueCountFrequency (%)
67991
79.8%
, 16428
 
19.3%
- 317
 
0.4%
' 138
 
0.2%
: 128
 
0.2%
( 71
 
0.1%
) 71
 
0.1%
. 54
 
0.1%
/ 15
 
< 0.1%
; 6
 
< 0.1%
Other values (3) 10
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 768435
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 84085
 
10.9%
n 73909
 
9.6%
67991
 
8.8%
i 54678
 
7.1%
s 52695
 
6.9%
a 48945
 
6.4%
c 44520
 
5.8%
o 43552
 
5.7%
t 37860
 
4.9%
r 37256
 
4.8%
Other values (53) 222944
29.0%

Year Found
Real number (ℝ)

MISSING 

Distinct106
Distinct (%)0.4%
Missing434
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean2004.5059
Minimum1819
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size228.1 KiB
2024-01-26T14:20:50.141904image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum1819
5-th percentile1978
Q11997
median2008
Q32014
95-th percentile2020
Maximum2023
Range204
Interquartile range (IQR)17

Descriptive statistics

Standard deviation13.464238
Coefficient of variation (CV)0.0067169858
Kurtosis4.4253388
Mean2004.5059
Median Absolute Deviation (MAD)8
Skewness-1.4558864
Sum57625536
Variance181.2857
MonotonicityNot monotonic
2024-01-26T14:20:50.223465image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2011 1301
 
4.5%
2007 1267
 
4.3%
2010 1227
 
4.2%
2008 1116
 
3.8%
2018 1112
 
3.8%
2019 1069
 
3.7%
2017 1053
 
3.6%
2006 962
 
3.3%
2016 958
 
3.3%
2015 953
 
3.3%
Other values (96) 17730
60.8%
ValueCountFrequency (%)
1819 1
 
< 0.1%
1887 2
< 0.1%
1890 1
 
< 0.1%
1898 1
 
< 0.1%
1906 1
 
< 0.1%
1908 2
< 0.1%
1910 1
 
< 0.1%
1911 1
 
< 0.1%
1912 2
< 0.1%
1917 3
< 0.1%
ValueCountFrequency (%)
2023 98
 
0.3%
2022 412
 
1.4%
2021 690
2.4%
2020 789
2.7%
2019 1069
3.7%
2018 1112
3.8%
2017 1053
3.6%
2016 958
3.3%
2015 953
3.3%
2014 930
3.2%

Entity Type
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size228.1 KiB
Subsidiary
20482 
Parent
8258 
Independent
 
432
Branch
 
10

Length

Max length11
Median length10
Mean length8.8815023
Min length6

Characters and Unicode

Total characters259180
Distinct characters18
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSubsidiary
2nd rowSubsidiary
3rd rowSubsidiary
4th rowSubsidiary
5th rowParent

Common Values

ValueCountFrequency (%)
Subsidiary 20482
70.2%
Parent 8258
28.3%
Independent 432
 
1.5%
Branch 10
 
< 0.1%

Length

2024-01-26T14:20:50.299753image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-26T14:20:50.376850image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
ValueCountFrequency (%)
subsidiary 20482
70.2%
parent 8258
28.3%
independent 432
 
1.5%
branch 10
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
i 40964
15.8%
a 28750
11.1%
r 28750
11.1%
d 21346
8.2%
S 20482
7.9%
b 20482
7.9%
s 20482
7.9%
y 20482
7.9%
u 20482
7.9%
n 9564
 
3.7%
Other values (8) 27396
10.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 229998
88.7%
Uppercase Letter 29182
 
11.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 40964
17.8%
a 28750
12.5%
r 28750
12.5%
d 21346
9.3%
b 20482
8.9%
s 20482
8.9%
y 20482
8.9%
u 20482
8.9%
n 9564
 
4.2%
e 9554
 
4.2%
Other values (4) 9142
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
S 20482
70.2%
P 8258
28.3%
I 432
 
1.5%
B 10
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 259180
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 40964
15.8%
a 28750
11.1%
r 28750
11.1%
d 21346
8.2%
S 20482
7.9%
b 20482
7.9%
s 20482
7.9%
y 20482
7.9%
u 20482
7.9%
n 9564
 
3.7%
Other values (8) 27396
10.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 259180
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 40964
15.8%
a 28750
11.1%
r 28750
11.1%
d 21346
8.2%
S 20482
7.9%
b 20482
7.9%
s 20482
7.9%
y 20482
7.9%
u 20482
7.9%
n 9564
 
3.7%
Other values (8) 27396
10.6%

Parent Company
Text

MISSING 

Distinct17882
Distinct (%)62.4%
Missing514
Missing (%)1.8%
Memory size228.1 KiB
2024-01-26T14:20:50.585136image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length86
Median length69
Mean length27.633319
Min length4

Characters and Unicode

Total characters792192
Distinct characters94
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12417 ?
Unique (%)43.3%

Sample

1st rowFRANK RECRUITMENT GROUP PRIVATE LTD.
2nd rowFORTITUDE SHIPPING PTE. LTD.
3rd rowMADISON LIGHTERS AND WATCHES CO LTD
4th rowWILMAR INTERNATIONAL LIMITED
5th rowASIA GREEN CAPITAL PTE. LTD.
ValueCountFrequency (%)
ltd 18644
 
15.4%
pte 17101
 
14.1%
limited 5626
 
4.6%
holdings 4514
 
3.7%
singapore 2003
 
1.7%
international 1762
 
1.5%
group 1693
 
1.4%
asia 1284
 
1.1%
private 1243
 
1.0%
holding 1150
 
0.9%
Other values (15332) 66313
54.7%
2024-01-26T14:20:50.894289image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
92665
 
11.7%
T 70730
 
8.9%
E 64579
 
8.2%
I 52253
 
6.6%
L 47055
 
5.9%
N 40467
 
5.1%
A 39288
 
5.0%
D 37004
 
4.7%
O 34577
 
4.4%
S 34036
 
4.3%
Other values (84) 279538
35.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 598708
75.6%
Space Separator 92665
 
11.7%
Lowercase Letter 57777
 
7.3%
Other Punctuation 35018
 
4.4%
Open Punctuation 3034
 
0.4%
Close Punctuation 3032
 
0.4%
Decimal Number 1069
 
0.1%
Dash Punctuation 810
 
0.1%
Math Symbol 38
 
< 0.1%
Modifier Letter 23
 
< 0.1%
Other values (2) 18
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 6311
10.9%
e 5924
10.3%
i 5625
9.7%
o 4792
 
8.3%
t 4766
 
8.2%
a 4637
 
8.0%
r 4003
 
6.9%
l 3264
 
5.6%
s 2883
 
5.0%
d 2409
 
4.2%
Other values (20) 13163
22.8%
Uppercase Letter
ValueCountFrequency (%)
T 70730
11.8%
E 64579
10.8%
I 52253
 
8.7%
L 47055
 
7.9%
N 40467
 
6.8%
A 39288
 
6.6%
D 37004
 
6.2%
O 34577
 
5.8%
S 34036
 
5.7%
P 33730
 
5.6%
Other values (18) 144989
24.2%
Other Punctuation
ValueCountFrequency (%)
. 32525
92.9%
, 1372
 
3.9%
& 929
 
2.7%
/ 97
 
0.3%
' 72
 
0.2%
* 10
 
< 0.1%
! 6
 
< 0.1%
@ 3
 
< 0.1%
? 2
 
< 0.1%
: 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 218
20.4%
2 217
20.3%
3 155
14.5%
0 147
13.8%
8 84
 
7.9%
9 73
 
6.8%
4 59
 
5.5%
7 40
 
3.7%
5 39
 
3.6%
6 37
 
3.5%
Other Symbol
ValueCountFrequency (%)
5
31.2%
3
18.8%
° 3
18.8%
2
 
12.5%
2
 
12.5%
1
 
6.2%
Math Symbol
ValueCountFrequency (%)
÷ 25
65.8%
+ 11
28.9%
2
 
5.3%
Space Separator
ValueCountFrequency (%)
92665
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3034
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3032
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 810
100.0%
Modifier Letter
ValueCountFrequency (%)
23
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 656402
82.9%
Common 135686
 
17.1%
Greek 104
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 70730
 
10.8%
E 64579
 
9.8%
I 52253
 
8.0%
L 47055
 
7.2%
N 40467
 
6.2%
A 39288
 
6.0%
D 37004
 
5.6%
O 34577
 
5.3%
S 34036
 
5.2%
P 33730
 
5.1%
Other values (43) 202683
30.9%
Common
ValueCountFrequency (%)
92665
68.3%
. 32525
 
24.0%
( 3034
 
2.2%
) 3032
 
2.2%
, 1372
 
1.0%
& 929
 
0.7%
- 810
 
0.6%
1 218
 
0.2%
2 217
 
0.2%
3 155
 
0.1%
Other values (26) 729
 
0.5%
Greek
ValueCountFrequency (%)
α 61
58.7%
Σ 29
27.9%
Θ 12
 
11.5%
φ 1
 
1.0%
δ 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 792019
> 99.9%
None 158
 
< 0.1%
Block Elements 8
 
< 0.1%
Box Drawing 5
 
< 0.1%
Misc Technical 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
92665
 
11.7%
T 70730
 
8.9%
E 64579
 
8.2%
I 52253
 
6.6%
L 47055
 
5.9%
N 40467
 
5.1%
A 39288
 
5.0%
D 37004
 
4.7%
O 34577
 
4.4%
S 34036
 
4.3%
Other values (68) 279365
35.3%
None
ValueCountFrequency (%)
α 61
38.6%
Σ 29
18.4%
÷ 25
15.8%
23
 
14.6%
Θ 12
 
7.6%
° 3
 
1.9%
µ 2
 
1.3%
φ 1
 
0.6%
δ 1
 
0.6%
· 1
 
0.6%
Block Elements
ValueCountFrequency (%)
5
62.5%
3
37.5%
Box Drawing
ValueCountFrequency (%)
2
40.0%
2
40.0%
1
20.0%
Misc Technical
ValueCountFrequency (%)
2
100.0%

Parent Country
Text

MISSING 

Distinct69
Distinct (%)0.2%
Missing520
Missing (%)1.8%
Memory size228.1 KiB
2024-01-26T14:20:51.020514image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length24
Median length9
Mean length9.2221059
Min length4

Characters and Unicode

Total characters264324
Distinct characters49
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)< 0.1%

Sample

1st rowSingapore
2nd rowSingapore
3rd rowHong Kong SAR
4th rowSingapore
5th rowSingapore
ValueCountFrequency (%)
singapore 21283
66.2%
united 1627
 
5.1%
japan 909
 
2.8%
states 829
 
2.6%
kingdom 762
 
2.4%
netherlands 481
 
1.5%
hong 470
 
1.5%
kong 470
 
1.5%
sar 470
 
1.5%
germany 429
 
1.3%
Other values (75) 4412
 
13.7%
2024-01-26T14:20:51.214061image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 29668
11.2%
n 29141
11.0%
i 26748
10.1%
e 26718
10.1%
r 24318
9.2%
o 23426
8.9%
g 23377
8.8%
S 23076
8.7%
p 22370
8.5%
t 4862
 
1.8%
Other values (39) 30620
11.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 227297
86.0%
Uppercase Letter 32992
 
12.5%
Space Separator 3480
 
1.3%
Open Punctuation 233
 
0.1%
Close Punctuation 233
 
0.1%
Other Punctuation 89
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 29668
13.1%
n 29141
12.8%
i 26748
11.8%
e 26718
11.8%
r 24318
10.7%
o 23426
10.3%
g 23377
10.3%
p 22370
9.8%
t 4862
 
2.1%
d 4499
 
2.0%
Other values (14) 12170
5.4%
Uppercase Letter
ValueCountFrequency (%)
S 23076
69.9%
U 1627
 
4.9%
K 1321
 
4.0%
I 993
 
3.0%
J 909
 
2.8%
A 813
 
2.5%
N 596
 
1.8%
R 562
 
1.7%
H 470
 
1.4%
C 463
 
1.4%
Other values (11) 2162
 
6.6%
Space Separator
ValueCountFrequency (%)
3480
100.0%
Open Punctuation
ValueCountFrequency (%)
( 233
100.0%
Close Punctuation
ValueCountFrequency (%)
) 233
100.0%
Other Punctuation
ValueCountFrequency (%)
, 89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 260289
98.5%
Common 4035
 
1.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 29668
11.4%
n 29141
11.2%
i 26748
10.3%
e 26718
10.3%
r 24318
9.3%
o 23426
9.0%
g 23377
9.0%
S 23076
8.9%
p 22370
8.6%
t 4862
 
1.9%
Other values (35) 26585
10.2%
Common
ValueCountFrequency (%)
3480
86.2%
( 233
 
5.8%
) 233
 
5.8%
, 89
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 264324
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 29668
11.2%
n 29141
11.0%
i 26748
10.1%
e 26718
10.1%
r 24318
9.2%
o 23426
8.9%
g 23377
8.8%
S 23076
8.7%
p 22370
8.5%
t 4862
 
1.8%
Other values (39) 30620
11.6%

Ownership Type
Categorical

IMBALANCE 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size228.1 KiB
Private
28250 
Public
 
825
Public Sector
 
49
Partnership
 
45
Non-Corporates
 
9

Length

Max length14
Median length7
Mean length6.990405
Min length6

Characters and Unicode

Total characters203994
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPrivate
2nd rowPrivate
3rd rowPrivate
4th rowPrivate
5th rowPrivate

Common Values

ValueCountFrequency (%)
Private 28250
96.8%
Public 825
 
2.8%
Public Sector 49
 
0.2%
Partnership 45
 
0.2%
Non-Corporates 9
 
< 0.1%
Nonprofit 4
 
< 0.1%

Length

2024-01-26T14:20:51.291222image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-26T14:20:51.373933image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
ValueCountFrequency (%)
private 28250
96.6%
public 874
 
3.0%
sector 49
 
0.2%
partnership 45
 
0.2%
non-corporates 9
 
< 0.1%
nonprofit 4
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
i 29173
14.3%
P 29169
14.3%
r 28411
13.9%
t 28357
13.9%
e 28353
13.9%
a 28304
13.9%
v 28250
13.8%
c 923
 
0.5%
u 874
 
0.4%
b 874
 
0.4%
Other values (12) 1306
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 174696
85.6%
Uppercase Letter 29240
 
14.3%
Space Separator 49
 
< 0.1%
Dash Punctuation 9
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 29173
16.7%
r 28411
16.3%
t 28357
16.2%
e 28353
16.2%
a 28304
16.2%
v 28250
16.2%
c 923
 
0.5%
u 874
 
0.5%
b 874
 
0.5%
l 874
 
0.5%
Other values (6) 303
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
P 29169
99.8%
S 49
 
0.2%
N 13
 
< 0.1%
C 9
 
< 0.1%
Space Separator
ValueCountFrequency (%)
49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 203936
> 99.9%
Common 58
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 29173
14.3%
P 29169
14.3%
r 28411
13.9%
t 28357
13.9%
e 28353
13.9%
a 28304
13.9%
v 28250
13.9%
c 923
 
0.5%
u 874
 
0.4%
b 874
 
0.4%
Other values (10) 1248
 
0.6%
Common
ValueCountFrequency (%)
49
84.5%
- 9
 
15.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 203994
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 29173
14.3%
P 29169
14.3%
r 28411
13.9%
t 28357
13.9%
e 28353
13.9%
a 28304
13.9%
v 28250
13.8%
c 923
 
0.5%
u 874
 
0.4%
b 874
 
0.4%
Other values (12) 1306
 
0.6%
Distinct28615
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size228.1 KiB
2024-01-26T14:20:51.561147image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length3455
Median length925
Mean length265.45775
Min length35

Characters and Unicode

Total characters7746588
Distinct characters82
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28599 ?
Unique (%)98.0%

Sample

1st rowFrank Consulting Services Private Limited is primarily engaged in providing employment services, except theatrical employment agencies and motion picture casting bureaus. Establishments classified here may assist either employers or those seeking employment.
2nd rowNew Desert Orchid Shipping Pte. Ltd. is primarily engaged in the transportation of freight on all inland waterways, including the intracoastal waterways on the Atlantic and Gulf Coasts.
3rd row2Mbao Biocellbank Pte. Ltd. is primarily engaged in holding or owning securities of companies other than banks, for the sole purpose of exercising some degree of control over the activities of the companies whose securities they hold.
4th rowNewbloom Pte. Ltd. is primarily engaged in holding or owning securities of companies other than banks, for the sole purpose of exercising some degree of control over the activities of the companies whose securities they hold.
5th rowAsia Green Capital Pte. Ltd. is primarily engaged in holding or owning securities of companies other than banks, for the sole purpose of exercising some degree of control over the activities of the companies whose securities they hold.
ValueCountFrequency (%)
of 56965
 
5.1%
and 53892
 
4.8%
the 42770
 
3.8%
in 39652
 
3.6%
primarily 29698
 
2.7%
engaged 29029
 
2.6%
is 28857
 
2.6%
pte 26112
 
2.3%
ltd 25975
 
2.3%
or 19600
 
1.8%
Other values (23583) 760770
68.3%
2024-01-26T14:20:51.852132image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1084138
14.0%
e 727764
 
9.4%
i 628694
 
8.1%
n 526740
 
6.8%
s 489769
 
6.3%
t 468463
 
6.0%
a 462071
 
6.0%
o 458801
 
5.9%
r 455299
 
5.9%
d 248877
 
3.2%
Other values (72) 2195972
28.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6304530
81.4%
Space Separator 1084138
 
14.0%
Other Punctuation 183370
 
2.4%
Uppercase Letter 148761
 
1.9%
Close Punctuation 7554
 
0.1%
Open Punctuation 7553
 
0.1%
Decimal Number 5421
 
0.1%
Dash Punctuation 5237
 
0.1%
Currency Symbol 22
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 32219
21.7%
L 30731
20.7%
S 14023
9.4%
T 8621
 
5.8%
A 8228
 
5.5%
C 8031
 
5.4%
I 6952
 
4.7%
E 6622
 
4.5%
H 5197
 
3.5%
M 4440
 
3.0%
Other values (18) 23697
15.9%
Lowercase Letter
ValueCountFrequency (%)
e 727764
11.5%
i 628694
 
10.0%
n 526740
 
8.4%
s 489769
 
7.8%
t 468463
 
7.4%
a 462071
 
7.3%
o 458801
 
7.3%
r 455299
 
7.2%
d 248877
 
3.9%
l 248291
 
3.9%
Other values (17) 1589761
25.2%
Other Punctuation
ValueCountFrequency (%)
. 83400
45.5%
, 77869
42.5%
; 18862
 
10.3%
' 1432
 
0.8%
& 1081
 
0.6%
: 289
 
0.2%
/ 190
 
0.1%
% 139
 
0.1%
" 102
 
0.1%
? 5
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 1370
25.3%
1 1231
22.7%
0 810
14.9%
3 660
12.2%
9 282
 
5.2%
6 233
 
4.3%
4 225
 
4.2%
5 221
 
4.1%
8 201
 
3.7%
7 188
 
3.5%
Space Separator
ValueCountFrequency (%)
1084138
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7554
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7553
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5237
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 22
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6453290
83.3%
Common 1293297
 
16.7%
Greek 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 727764
11.3%
i 628694
 
9.7%
n 526740
 
8.2%
s 489769
 
7.6%
t 468463
 
7.3%
a 462071
 
7.2%
o 458801
 
7.1%
r 455299
 
7.1%
d 248877
 
3.9%
l 248291
 
3.8%
Other values (44) 1738521
26.9%
Common
ValueCountFrequency (%)
1084138
83.8%
. 83400
 
6.4%
, 77869
 
6.0%
; 18862
 
1.5%
) 7554
 
0.6%
( 7553
 
0.6%
- 5237
 
0.4%
' 1432
 
0.1%
2 1370
 
0.1%
1 1231
 
0.1%
Other values (17) 4651
 
0.4%
Greek
ValueCountFrequency (%)
Σ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7746221
> 99.9%
None 367
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1084138
14.0%
e 727764
 
9.4%
i 628694
 
8.1%
n 526740
 
6.8%
s 489769
 
6.3%
t 468463
 
6.0%
a 462071
 
6.0%
o 458801
 
5.9%
r 455299
 
5.9%
d 248877
 
3.2%
Other values (69) 2195605
28.3%
None
ValueCountFrequency (%)
á 328
89.4%
Æ 38
 
10.4%
Σ 1
 
0.3%

Square Footage
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29182
Missing (%)100.0%
Memory size228.1 KiB

Company Status (Active/Inactive)
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size228.1 KiB
Active
29182 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters175092
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowActive
2nd rowActive
3rd rowActive
4th rowActive
5th rowActive

Common Values

ValueCountFrequency (%)
Active 29182
100.0%

Length

2024-01-26T14:20:51.927564image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-26T14:20:51.988989image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
ValueCountFrequency (%)
active 29182
100.0%

Most occurring characters

ValueCountFrequency (%)
A 29182
16.7%
c 29182
16.7%
t 29182
16.7%
i 29182
16.7%
v 29182
16.7%
e 29182
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 145910
83.3%
Uppercase Letter 29182
 
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 29182
20.0%
t 29182
20.0%
i 29182
20.0%
v 29182
20.0%
e 29182
20.0%
Uppercase Letter
ValueCountFrequency (%)
A 29182
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 175092
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 29182
16.7%
c 29182
16.7%
t 29182
16.7%
i 29182
16.7%
v 29182
16.7%
e 29182
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 175092
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 29182
16.7%
c 29182
16.7%
t 29182
16.7%
i 29182
16.7%
v 29182
16.7%
e 29182
16.7%

Employees (Single Site)
Real number (ℝ)

MISSING  SKEWED 

Distinct227
Distinct (%)1.4%
Missing12403
Missing (%)42.5%
Infinite0
Infinite (%)0.0%
Mean36.856189
Minimum1
Maximum12000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size228.1 KiB
2024-01-26T14:20:52.046479image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q110
median16
Q329
95-th percentile100
Maximum12000
Range11999
Interquartile range (IQR)19

Descriptive statistics

Standard deviation173.33442
Coefficient of variation (CV)4.7029935
Kurtosis1888.0192
Mean36.856189
Median Absolute Deviation (MAD)6
Skewness36.260684
Sum618410
Variance30044.821
MonotonicityNot monotonic
2024-01-26T14:20:52.129922image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 3523
 
12.1%
11 1447
 
5.0%
20 1258
 
4.3%
25 1180
 
4.0%
15 985
 
3.4%
30 701
 
2.4%
21 460
 
1.6%
50 348
 
1.2%
32 341
 
1.2%
5 340
 
1.2%
Other values (217) 6196
21.2%
(Missing) 12403
42.5%
ValueCountFrequency (%)
1 282
 
1.0%
2 263
 
0.9%
3 245
 
0.8%
4 218
 
0.7%
5 340
 
1.2%
6 178
 
0.6%
7 139
 
0.5%
8 205
 
0.7%
9 150
 
0.5%
10 3523
12.1%
ValueCountFrequency (%)
12000 1
< 0.1%
7500 1
< 0.1%
6500 1
< 0.1%
6000 1
< 0.1%
5000 2
< 0.1%
4323 1
< 0.1%
3000 2
< 0.1%
2800 1
< 0.1%
2533 1
< 0.1%
2500 1
< 0.1%

Employees (Domestic Ultimate Total)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct380
Distinct (%)1.3%
Missing79
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean139.76418
Minimum1
Maximum80000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size228.1 KiB
2024-01-26T14:20:52.214198image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q14
median16
Q360
95-th percentile400
Maximum80000
Range79999
Interquartile range (IQR)56

Descriptive statistics

Standard deviation1118.9392
Coefficient of variation (CV)8.0059085
Kurtosis2058.1394
Mean139.76418
Median Absolute Deviation (MAD)12
Skewness36.216419
Sum4067557
Variance1252025
MonotonicityNot monotonic
2024-01-26T14:20:52.399681image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 6474
22.2%
100 2050
 
7.0%
10 1921
 
6.6%
50 1469
 
5.0%
20 1287
 
4.4%
5 1260
 
4.3%
30 903
 
3.1%
15 796
 
2.7%
80 776
 
2.7%
11 653
 
2.2%
Other values (370) 11514
39.5%
ValueCountFrequency (%)
1 198
 
0.7%
2 531
 
1.8%
3 534
 
1.8%
4 6474
22.2%
5 1260
 
4.3%
6 445
 
1.5%
7 325
 
1.1%
8 585
 
2.0%
9 145
 
0.5%
10 1921
 
6.6%
ValueCountFrequency (%)
80000 2
 
< 0.1%
40000 2
 
< 0.1%
35000 3
 
< 0.1%
22222 8
< 0.1%
12782 3
 
< 0.1%
12744 19
0.1%
12000 14
< 0.1%
11345 15
0.1%
10500 8
< 0.1%
9988 2
 
< 0.1%

Employees (Global Ultimate Total)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct2013
Distinct (%)7.6%
Missing2774
Missing (%)9.5%
Infinite0
Infinite (%)0.0%
Mean6994.6646
Minimum1
Maximum2190000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size228.1 KiB
2024-01-26T14:20:52.486783image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q14
median15
Q3100
95-th percentile23000
Maximum2190000
Range2189999
Interquartile range (IQR)96

Descriptive statistics

Standard deviation45394.62
Coefficient of variation (CV)6.4898924
Kurtosis645.6766
Mean6994.6646
Median Absolute Deviation (MAD)12
Skewness19.101968
Sum1.847151 × 108
Variance2.0606716 × 109
MonotonicityNot monotonic
2024-01-26T14:20:52.564347image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 6435
22.1%
100 2002
 
6.9%
10 1344
 
4.6%
3 1205
 
4.1%
5 986
 
3.4%
80 743
 
2.5%
15 673
 
2.3%
20 636
 
2.2%
2 587
 
2.0%
8 495
 
1.7%
Other values (2003) 11302
38.7%
(Missing) 2774
 
9.5%
ValueCountFrequency (%)
1 193
 
0.7%
2 587
 
2.0%
3 1205
 
4.1%
4 6435
22.1%
5 986
 
3.4%
6 392
 
1.3%
7 280
 
1.0%
8 495
 
1.7%
9 130
 
0.4%
10 1344
 
4.6%
ValueCountFrequency (%)
2190000 2
 
< 0.1%
1541000 4
 
< 0.1%
669275 7
 
< 0.1%
589109 10
< 0.1%
570060 1
 
< 0.1%
536000 4
 
< 0.1%
529000 2
 
< 0.1%
440000 1
 
< 0.1%
402000 2
 
< 0.1%
400000 18
0.1%

Sales (Domestic Ultimate Total USD)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct8346
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.5209921 × 108
Minimum-1.502631 × 108
Maximum3.184764 × 1011
Zeros0
Zeros (%)0.0%
Negative3
Negative (%)< 0.1%
Memory size228.1 KiB
2024-01-26T14:20:52.643771image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum-1.502631 × 108
5-th percentile327369
Q11026308
median2606644
Q321769690
95-th percentile9.70319 × 108
Maximum3.184764 × 1011
Range3.1862666 × 1011
Interquartile range (IQR)20743382

Descriptive statistics

Standard deviation1.0196357 × 1010
Coefficient of variation (CV)13.557197
Kurtosis780.95227
Mean7.5209921 × 108
Median Absolute Deviation (MAD)2221659
Skewness26.264112
Sum2.1947759 × 1013
Variance1.0396569 × 1020
MonotonicityNot monotonic
2024-01-26T14:20:52.725829image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1026308 5977
 
20.5%
13076800 615
 
2.1%
384985 597
 
2.0%
2565770 426
 
1.5%
12828850 425
 
1.5%
18443540 364
 
1.2%
769731 278
 
1.0%
660690 272
 
0.9%
233248 186
 
0.6%
3162096 162
 
0.6%
Other values (8336) 19880
68.1%
ValueCountFrequency (%)
-150263100 1
 
< 0.1%
-453533 1
 
< 0.1%
-166798 1
 
< 0.1%
46 2
 
< 0.1%
137 1
 
< 0.1%
139 2
 
< 0.1%
153 1
 
< 0.1%
168 2
 
< 0.1%
193 6
< 0.1%
496 1
 
< 0.1%
ValueCountFrequency (%)
3.184764 × 10112
 
< 0.1%
3.18 × 101122
 
0.1%
1.71 × 10111
 
< 0.1%
1.16 × 10111
 
< 0.1%
1.14 × 10111
 
< 0.1%
9.527987263 × 10106
 
< 0.1%
7.3398976 × 101082
0.3%
4.9200551 × 10101
 
< 0.1%
4.2489921 × 10101
 
< 0.1%
3.766219363 × 10101
 
< 0.1%

Sales (Global Ultimate Total USD)
Real number (ℝ)

HIGH CORRELATION 

Distinct7574
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9317714 × 109
Minimum1
Maximum5.14 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size228.1 KiB
2024-01-26T14:20:52.809413image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile327369
Q11026308
median3259582.5
Q31.4822582 × 108
95-th percentile1.5829213 × 1010
Maximum5.14 × 1011
Range5.14 × 1011
Interquartile range (IQR)1.4719951 × 108

Descriptive statistics

Standard deviation2.1845886 × 1010
Coefficient of variation (CV)5.5562452
Kurtosis170.12266
Mean3.9317714 × 109
Median Absolute Deviation (MAD)2968924.5
Skewness11.341881
Sum1.1473695 × 1014
Variance4.7724273 × 1020
MonotonicityNot monotonic
2024-01-26T14:20:52.889941image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1026308 6026
 
20.6%
467565 742
 
2.5%
13076800 671
 
2.3%
384985 607
 
2.1%
18443540 377
 
1.3%
660690 275
 
0.9%
769731 272
 
0.9%
2668710 224
 
0.8%
355828 218
 
0.7%
233248 186
 
0.6%
Other values (7564) 19584
67.1%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
27 1
< 0.1%
137 1
< 0.1%
139 2
< 0.1%
364 1
< 0.1%
541 2
< 0.1%
839 1
< 0.1%
1039 1
< 0.1%
1262 2
< 0.1%
ValueCountFrequency (%)
5.14 × 10111
 
< 0.1%
5.13983 × 10113
 
< 0.1%
4.14 × 10111
 
< 0.1%
4.1368 × 10112
 
< 0.1%
3.94 × 10111
 
< 0.1%
3.81314 × 10113
 
< 0.1%
3.81 × 101119
0.1%
3.24162 × 10111
 
< 0.1%
3.22467 × 10111
 
< 0.1%
3.02 × 101111
< 0.1%

Import/Export Status
Categorical

MISSING 

Distinct3
Distinct (%)< 0.1%
Missing22569
Missing (%)77.3%
Memory size228.1 KiB
Both Imports & Exports
4254 
Exports
1681 
Imports
678 

Length

Max length22
Median length22
Mean length16.649176
Min length7

Characters and Unicode

Total characters110101
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowExports
2nd rowBoth Imports & Exports
3rd rowBoth Imports & Exports
4th rowBoth Imports & Exports
5th rowBoth Imports & Exports

Common Values

ValueCountFrequency (%)
Both Imports & Exports 4254
 
14.6%
Exports 1681
 
5.8%
Imports 678
 
2.3%
(Missing) 22569
77.3%

Length

2024-01-26T14:20:52.968875image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-26T14:20:53.042516image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
ValueCountFrequency (%)
exports 5935
30.6%
imports 4932
25.5%
both 4254
22.0%
4254
22.0%

Most occurring characters

ValueCountFrequency (%)
o 15121
13.7%
t 15121
13.7%
12762
11.6%
p 10867
9.9%
r 10867
9.9%
s 10867
9.9%
E 5935
 
5.4%
x 5935
 
5.4%
I 4932
 
4.5%
m 4932
 
4.5%
Other values (3) 12762
11.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 77964
70.8%
Uppercase Letter 15121
 
13.7%
Space Separator 12762
 
11.6%
Other Punctuation 4254
 
3.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 15121
19.4%
t 15121
19.4%
p 10867
13.9%
r 10867
13.9%
s 10867
13.9%
x 5935
 
7.6%
m 4932
 
6.3%
h 4254
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
E 5935
39.3%
I 4932
32.6%
B 4254
28.1%
Space Separator
ValueCountFrequency (%)
12762
100.0%
Other Punctuation
ValueCountFrequency (%)
& 4254
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 93085
84.5%
Common 17016
 
15.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 15121
16.2%
t 15121
16.2%
p 10867
11.7%
r 10867
11.7%
s 10867
11.7%
E 5935
 
6.4%
x 5935
 
6.4%
I 4932
 
5.3%
m 4932
 
5.3%
B 4254
 
4.6%
Common
ValueCountFrequency (%)
12762
75.0%
& 4254
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 110101
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 15121
13.7%
t 15121
13.7%
12762
11.6%
p 10867
9.9%
r 10867
9.9%
s 10867
9.9%
E 5935
 
5.4%
x 5935
 
5.4%
I 4932
 
4.5%
m 4932
 
4.5%
Other values (3) 12762
11.6%

Fiscal Year End
Date

MISSING 

Distinct115
Distinct (%)1.7%
Missing22445
Missing (%)76.9%
Memory size228.1 KiB
Minimum2018-01-31 05:00:00+00:00
Maximum2023-06-30 04:00:00+00:00
2024-01-26T14:20:53.110805image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2024-01-26T14:20:53.187703image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct14145
Distinct (%)49.3%
Missing514
Missing (%)1.8%
Memory size228.1 KiB
2024-01-26T14:20:53.394816image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length119
Median length83
Mean length26.54008
Min length3

Characters and Unicode

Total characters760851
Distinct characters91
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8639 ?
Unique (%)30.1%

Sample

1st rowFINDERS HOLDCO LIMITED
2nd rowPETREDEC PTE. LIMITED
3rd rowMADISON LIGHTERS AND WATCHES CO LTD
4th rowWILMAR INTERNATIONAL LIMITED
5th rowASIA GREEN CAPITAL PTE. LTD.
ValueCountFrequency (%)
ltd 16312
 
14.0%
pte 14468
 
12.5%
limited 5560
 
4.8%
holdings 4762
 
4.1%
group 2031
 
1.7%
singapore 1671
 
1.4%
corporation 1516
 
1.3%
inc 1330
 
1.1%
international 1214
 
1.0%
private 1188
 
1.0%
Other values (13722) 66138
56.9%
2024-01-26T14:20:53.696475image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
87522
 
11.5%
T 62890
 
8.3%
E 58598
 
7.7%
I 50071
 
6.6%
L 42971
 
5.6%
N 37406
 
4.9%
A 35041
 
4.6%
D 33772
 
4.4%
O 32894
 
4.3%
S 31350
 
4.1%
Other values (81) 288336
37.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 555144
73.0%
Space Separator 87522
 
11.5%
Lowercase Letter 77907
 
10.2%
Other Punctuation 33229
 
4.4%
Open Punctuation 2495
 
0.3%
Close Punctuation 2494
 
0.3%
Decimal Number 1048
 
0.1%
Dash Punctuation 818
 
0.1%
Math Symbol 105
 
< 0.1%
Other Symbol 50
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 8374
10.7%
e 7633
9.8%
o 7339
 
9.4%
i 7266
 
9.3%
t 6321
 
8.1%
a 5780
 
7.4%
r 5668
 
7.3%
s 3974
 
5.1%
l 3892
 
5.0%
d 3213
 
4.1%
Other values (20) 18447
23.7%
Uppercase Letter
ValueCountFrequency (%)
T 62890
11.3%
E 58598
10.6%
I 50071
 
9.0%
L 42971
 
7.7%
N 37406
 
6.7%
A 35041
 
6.3%
D 33772
 
6.1%
O 32894
 
5.9%
S 31350
 
5.6%
P 30918
 
5.6%
Other values (19) 139233
25.1%
Decimal Number
ValueCountFrequency (%)
2 222
21.2%
0 186
17.7%
1 185
17.7%
3 155
14.8%
8 64
 
6.1%
9 60
 
5.7%
4 60
 
5.7%
5 43
 
4.1%
7 37
 
3.5%
6 36
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 29747
89.5%
, 1921
 
5.8%
& 970
 
2.9%
' 529
 
1.6%
/ 47
 
0.1%
* 10
 
< 0.1%
@ 2
 
< 0.1%
! 2
 
< 0.1%
: 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
÷ 89
84.8%
+ 14
 
13.3%
± 1
 
1.0%
1
 
1.0%
Other Symbol
ValueCountFrequency (%)
° 37
74.0%
8
 
16.0%
4
 
8.0%
1
 
2.0%
Space Separator
ValueCountFrequency (%)
87522
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2495
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2494
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 818
100.0%
Modifier Letter
ValueCountFrequency (%)
39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 632952
83.2%
Common 127763
 
16.8%
Greek 136
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 62890
 
9.9%
E 58598
 
9.3%
I 50071
 
7.9%
L 42971
 
6.8%
N 37406
 
5.9%
A 35041
 
5.5%
D 33772
 
5.3%
O 32894
 
5.2%
S 31350
 
5.0%
P 30918
 
4.9%
Other values (44) 217041
34.3%
Common
ValueCountFrequency (%)
87522
68.5%
. 29747
 
23.3%
( 2495
 
2.0%
) 2494
 
2.0%
, 1921
 
1.5%
& 970
 
0.8%
- 818
 
0.6%
' 529
 
0.4%
2 222
 
0.2%
0 186
 
0.1%
Other values (22) 859
 
0.7%
Greek
ValueCountFrequency (%)
α 62
45.6%
Σ 51
37.5%
Θ 20
 
14.7%
Φ 2
 
1.5%
σ 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 760530
> 99.9%
None 307
 
< 0.1%
Block Elements 12
 
< 0.1%
Box Drawing 1
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
87522
 
11.5%
T 62890
 
8.3%
E 58598
 
7.7%
I 50071
 
6.6%
L 42971
 
5.7%
N 37406
 
4.9%
A 35041
 
4.6%
D 33772
 
4.4%
O 32894
 
4.3%
S 31350
 
4.1%
Other values (66) 288015
37.9%
None
ValueCountFrequency (%)
÷ 89
29.0%
α 62
20.2%
Σ 51
16.6%
39
12.7%
° 37
12.1%
Θ 20
 
6.5%
ß 3
 
1.0%
µ 2
 
0.7%
Φ 2
 
0.7%
± 1
 
0.3%
Block Elements
ValueCountFrequency (%)
8
66.7%
4
33.3%
Box Drawing
ValueCountFrequency (%)
1
100.0%
Math Operators
ValueCountFrequency (%)
1
100.0%
Distinct74
Distinct (%)0.3%
Missing523
Missing (%)1.8%
Memory size228.1 KiB
2024-01-26T14:20:53.818145image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length24
Median length9
Mean length9.2855996
Min length4

Characters and Unicode

Total characters266116
Distinct characters50
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)< 0.1%

Sample

1st rowUnited Kingdom
2nd rowSingapore
3rd rowHong Kong SAR
4th rowSingapore
5th rowSingapore
ValueCountFrequency (%)
singapore 19234
58.3%
united 2454
 
7.4%
states 1590
 
4.8%
japan 1232
 
3.7%
kingdom 815
 
2.5%
islands 735
 
2.2%
germany 536
 
1.6%
india 458
 
1.4%
virgin 448
 
1.4%
british 448
 
1.4%
Other values (80) 5025
 
15.2%
2024-01-26T14:20:54.022351image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 30791
11.6%
n 28840
10.8%
i 27047
10.2%
e 26393
9.9%
r 22990
8.6%
S 21439
8.1%
g 21070
7.9%
o 20993
7.9%
p 20699
7.8%
t 7273
 
2.7%
Other values (40) 38581
14.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 227590
85.5%
Uppercase Letter 33201
 
12.5%
Space Separator 4316
 
1.6%
Close Punctuation 448
 
0.2%
Open Punctuation 448
 
0.2%
Other Punctuation 113
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 30791
13.5%
n 28840
12.7%
i 27047
11.9%
e 26393
11.6%
r 22990
10.1%
g 21070
9.3%
o 20993
9.2%
p 20699
9.1%
t 7273
 
3.2%
d 5666
 
2.5%
Other values (14) 15828
7.0%
Uppercase Letter
ValueCountFrequency (%)
S 21439
64.6%
U 2454
 
7.4%
I 1417
 
4.3%
J 1233
 
3.7%
K 1100
 
3.3%
C 863
 
2.6%
B 696
 
2.1%
A 546
 
1.6%
G 537
 
1.6%
M 512
 
1.5%
Other values (12) 2404
 
7.2%
Space Separator
ValueCountFrequency (%)
4316
100.0%
Close Punctuation
ValueCountFrequency (%)
) 448
100.0%
Open Punctuation
ValueCountFrequency (%)
( 448
100.0%
Other Punctuation
ValueCountFrequency (%)
, 113
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 260791
98.0%
Common 5325
 
2.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 30791
11.8%
n 28840
11.1%
i 27047
10.4%
e 26393
10.1%
r 22990
8.8%
S 21439
8.2%
g 21070
8.1%
o 20993
8.0%
p 20699
7.9%
t 7273
 
2.8%
Other values (36) 33256
12.8%
Common
ValueCountFrequency (%)
4316
81.1%
) 448
 
8.4%
( 448
 
8.4%
, 113
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 266116
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 30791
11.6%
n 28840
10.8%
i 27047
10.2%
e 26393
9.9%
r 22990
8.6%
S 21439
8.1%
g 21070
7.9%
o 20993
7.9%
p 20699
7.8%
t 7273
 
2.7%
Other values (40) 38581
14.5%
Distinct15597
Distinct (%)55.4%
Missing1035
Missing (%)3.5%
Memory size228.1 KiB
2024-01-26T14:20:54.204785image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length89
Median length67
Mean length29.027037
Min length8

Characters and Unicode

Total characters817024
Distinct characters49
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10700 ?
Unique (%)38.0%

Sample

1st rowFRANK RECRUITMENT GROUP PRIVATE LTD.
2nd row2MBAO BIOCELLBANK PTE. LTD.
3rd rowWILMAR INTERNATIONAL LIMITED
4th rowASIA GREEN CAPITAL PTE. LTD.
5th rowQUETZAL CAPITAL PTE. LTD.
ValueCountFrequency (%)
ltd 22946
 
18.1%
pte 22499
 
17.8%
singapore 5233
 
4.1%
limited 4372
 
3.5%
holdings 4177
 
3.3%
asia 2389
 
1.9%
group 1479
 
1.2%
international 1364
 
1.1%
private 1283
 
1.0%
investment 945
 
0.7%
Other values (14110) 59774
47.3%
2024-01-26T14:20:54.502384image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
98314
12.0%
T 81343
 
10.0%
E 76075
 
9.3%
I 57727
 
7.1%
L 50029
 
6.1%
A 45362
 
5.6%
N 45008
 
5.5%
P 42529
 
5.2%
D 40068
 
4.9%
S 39853
 
4.9%
Other values (39) 240716
29.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 669335
81.9%
Space Separator 98314
 
12.0%
Other Punctuation 39480
 
4.8%
Open Punctuation 4055
 
0.5%
Close Punctuation 4054
 
0.5%
Decimal Number 1029
 
0.1%
Dash Punctuation 752
 
0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 81343
12.2%
E 76075
11.4%
I 57727
 
8.6%
L 50029
 
7.5%
A 45362
 
6.8%
N 45008
 
6.7%
P 42529
 
6.4%
D 40068
 
6.0%
S 39853
 
6.0%
O 38167
 
5.7%
Other values (16) 153174
22.9%
Decimal Number
ValueCountFrequency (%)
2 215
20.9%
1 193
18.8%
0 179
17.4%
3 150
14.6%
8 68
 
6.6%
9 63
 
6.1%
4 49
 
4.8%
6 38
 
3.7%
7 38
 
3.7%
5 36
 
3.5%
Other Punctuation
ValueCountFrequency (%)
. 37903
96.0%
& 821
 
2.1%
' 654
 
1.7%
, 86
 
0.2%
* 10
 
< 0.1%
/ 3
 
< 0.1%
! 2
 
< 0.1%
: 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
98314
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4055
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4054
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 752
100.0%
Math Symbol
ValueCountFrequency (%)
+ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 669335
81.9%
Common 147689
 
18.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 81343
12.2%
E 76075
11.4%
I 57727
 
8.6%
L 50029
 
7.5%
A 45362
 
6.8%
N 45008
 
6.7%
P 42529
 
6.4%
D 40068
 
6.0%
S 39853
 
6.0%
O 38167
 
5.7%
Other values (16) 153174
22.9%
Common
ValueCountFrequency (%)
98314
66.6%
. 37903
 
25.7%
( 4055
 
2.7%
) 4054
 
2.7%
& 821
 
0.6%
- 752
 
0.5%
' 654
 
0.4%
2 215
 
0.1%
1 193
 
0.1%
0 179
 
0.1%
Other values (13) 549
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 817024
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
98314
12.0%
T 81343
 
10.0%
E 76075
 
9.3%
I 57727
 
7.1%
L 50029
 
6.1%
A 45362
 
5.6%
N 45008
 
5.5%
P 42529
 
5.2%
D 40068
 
4.9%
S 39853
 
4.9%
Other values (39) 240716
29.5%

Is Domestic Ultimate
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size228.1 KiB
1.0
14593 
0.0
14589 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters87546
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row1.0
4th row0.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 14593
50.0%
0.0 14589
50.0%

Length

2024-01-26T14:20:54.580047image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-26T14:20:54.643476image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 14593
50.0%
0.0 14589
50.0%

Most occurring characters

ValueCountFrequency (%)
0 43771
50.0%
. 29182
33.3%
1 14593
 
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58364
66.7%
Other Punctuation 29182
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43771
75.0%
1 14593
 
25.0%
Other Punctuation
ValueCountFrequency (%)
. 29182
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 87546
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43771
50.0%
. 29182
33.3%
1 14593
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 87546
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43771
50.0%
. 29182
33.3%
1 14593
 
16.7%

Is Global Ultimate
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size228.1 KiB
0.0
21675 
1.0
7507 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters87546
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row1.0

Common Values

ValueCountFrequency (%)
0.0 21675
74.3%
1.0 7507
 
25.7%

Length

2024-01-26T14:20:54.697954image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-26T14:20:54.760569image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
ValueCountFrequency (%)
0.0 21675
74.3%
1.0 7507
 
25.7%

Most occurring characters

ValueCountFrequency (%)
0 50857
58.1%
. 29182
33.3%
1 7507
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58364
66.7%
Other Punctuation 29182
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 50857
87.1%
1 7507
 
12.9%
Other Punctuation
ValueCountFrequency (%)
. 29182
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 87546
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 50857
58.1%
. 29182
33.3%
1 7507
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 87546
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 50857
58.1%
. 29182
33.3%
1 7507
 
8.6%

Interactions

2024-01-26T14:20:45.956077image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
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2024-01-26T14:20:42.078998image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2024-01-26T14:20:42.831564image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2024-01-26T14:20:43.561739image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2024-01-26T14:20:44.330356image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2024-01-26T14:20:45.055468image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2024-01-26T14:20:45.881142image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Correlations

2024-01-26T14:20:54.821836image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
LATITUDELONGITUDESIC Code8-Digit SIC CodeYear FoundEmployees (Single Site)Employees (Domestic Ultimate Total)Employees (Global Ultimate Total)Sales (Domestic Ultimate Total USD)Sales (Global Ultimate Total USD)Entity TypeOwnership TypeImport/Export StatusIs Domestic UltimateIs Global Ultimate
LATITUDE1.0000.081-0.093-0.086-0.0400.1480.0710.0660.0250.0200.0290.0000.0000.0140.040
LONGITUDE0.0811.0000.0050.006-0.0060.037-0.0030.000-0.005-0.0030.0250.0010.0090.0100.036
SIC Code-0.0930.0051.0000.9960.227-0.225-0.149-0.126-0.233-0.1650.1380.1520.3730.0930.186
8-Digit SIC Code-0.0860.0060.9961.0000.210-0.224-0.136-0.115-0.221-0.1560.1380.1520.3730.0930.186
Year Found-0.040-0.0060.2270.2101.000-0.093-0.259-0.234-0.297-0.2470.0750.1270.0680.0560.117
Employees (Single Site)0.1480.037-0.225-0.224-0.0931.0000.3130.1110.1670.0870.0000.0370.0060.0000.000
Employees (Domestic Ultimate Total)0.071-0.003-0.149-0.136-0.2590.3131.0000.7390.7250.5750.0280.0000.0000.0390.018
Employees (Global Ultimate Total)0.0660.000-0.126-0.115-0.2340.1110.7391.0000.5700.8410.0380.0000.0170.0530.057
Sales (Domestic Ultimate Total USD)0.025-0.005-0.233-0.221-0.2970.1670.7250.5701.0000.6900.0170.0000.0080.0580.035
Sales (Global Ultimate Total USD)0.020-0.003-0.165-0.156-0.2470.0870.5750.8410.6901.0000.0470.0000.0000.0420.082
Entity Type0.0290.0250.1380.1380.0750.0000.0280.0380.0170.0471.0000.0750.0350.5190.937
Ownership Type0.0000.0010.1520.1520.1270.0370.0000.0000.0000.0000.0751.0000.0430.0630.107
Import/Export Status0.0000.0090.3730.3730.0680.0060.0000.0170.0080.0000.0350.0431.0000.1080.055
Is Domestic Ultimate0.0140.0100.0930.0930.0560.0000.0390.0530.0580.0420.5190.0630.1081.0000.588
Is Global Ultimate0.0400.0360.1860.1860.1170.0000.0180.0570.0350.0820.9370.1070.0550.5881.000

Missing values

2024-01-26T14:20:46.755515image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-26T14:20:47.048643image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-01-26T14:20:47.343595image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

LATITUDELONGITUDEAccountIDCompanySIC CodeIndustry8-Digit SIC Code8-Digit SIC DescriptionYear FoundEntity TypeParent CompanyParent CountryOwnership TypeCompany DescriptionSquare FootageCompany Status (Active/Inactive)Employees (Single Site)Employees (Domestic Ultimate Total)Employees (Global Ultimate Total)Sales (Domestic Ultimate Total USD)Sales (Global Ultimate Total USD)Import/Export StatusFiscal Year EndGlobal Ultimate CompanyGlobal Ultimate CountryDomestic Ultimate CompanyIs Domestic UltimateIs Global Ultimate
01.285495103.843852LAKB2BID4559214FRANK CONSULTING SERVICES PRIVATE LIMITED7361.0Employment Agencies73610000.0Employment agencies2020.0SubsidiaryFRANK RECRUITMENT GROUP PRIVATE LTD.SingaporePrivateFrank Consulting Services Private Limited is primarily engaged in providing employment services, except theatrical employment agencies and motion picture casting bureaus. Establishments classified here may assist either employers or those seeking employment.NaNActive15.025.0NaN2.209224e+064.637871e+06NaNNaNFINDERS HOLDCO LIMITEDUnited KingdomFRANK RECRUITMENT GROUP PRIVATE LTD.0.00.0
11.291294103.827476LAKB2BID7610849NEW DESERT ORCHID SHIPPING PTE. LTD.4449.0Water Transportation of Freight, Not Elsewhere Classified44490000.0Water transportation of freight2015.0SubsidiaryFORTITUDE SHIPPING PTE. LTD.SingaporePrivateNew Desert Orchid Shipping Pte. Ltd. is primarily engaged in the transportation of freight on all inland waterways, including the intracoastal waterways on the Atlantic and Gulf Coasts.NaNActive39.0100.0100.07.093536e+097.093536e+09NaNNaNPETREDEC PTE. LIMITEDSingaporeNaN0.00.0
21.300144103.857517LAKB2BID54616792MBAO BIOCELLBANK PTE. LTD.6719.0Offices of Holding Companies, Not Elsewhere Classified67190000.0Holding companies, nec1993.0SubsidiaryMADISON LIGHTERS AND WATCHES CO LTDHong Kong SARPrivate2Mbao Biocellbank Pte. Ltd. is primarily engaged in holding or owning securities of companies other than banks, for the sole purpose of exercising some degree of control over the activities of the companies whose securities they hold.NaNActive4.04.04.01.026308e+061.026308e+06NaNNaNMADISON LIGHTERS AND WATCHES CO LTDHong Kong SAR2MBAO BIOCELLBANK PTE. LTD.1.00.0
31.300785103.791263LAKB2BID5088529NEWBLOOM PTE. LTD.6719.0Offices of Holding Companies, Not Elsewhere Classified67190000.0Holding companies, nec2006.0SubsidiaryWILMAR INTERNATIONAL LIMITEDSingaporePrivateNewbloom Pte. Ltd. is primarily engaged in holding or owning securities of companies other than banks, for the sole purpose of exercising some degree of control over the activities of the companies whose securities they hold.NaNActive10.0100.0100.07.339898e+107.339898e+10NaNNaNWILMAR INTERNATIONAL LIMITEDSingaporeWILMAR INTERNATIONAL LIMITED0.00.0
41.298759103.859430LAKB2BID1268831ASIA GREEN CAPITAL PTE. LTD.6719.0Offices of Holding Companies, Not Elsewhere Classified67190000.0Holding companies, nec2006.0ParentASIA GREEN CAPITAL PTE. LTD.SingaporePrivateAsia Green Capital Pte. Ltd. is primarily engaged in holding or owning securities of companies other than banks, for the sole purpose of exercising some degree of control over the activities of the companies whose securities they hold.NaNActiveNaN4.04.04.322130e+054.322130e+05ExportsNaNASIA GREEN CAPITAL PTE. LTD.SingaporeASIA GREEN CAPITAL PTE. LTD.1.01.0
51.444773103.812740LAKB2BID2264578SEMCO SALVAGE (V) PTE LTD4959.0Sanitary Services, Not Elsewhere Classified49590000.0Sanitary services, nec1986.0SubsidiaryPACC OFFSHORE SERVICES HOLDINGS LTD.SingaporePrivateSemco Salvage (V) Pte Ltd is primarily engaged in furnishing sanitary services, not elsewhere classified.NaNActive300.04.04.01.026308e+061.026308e+06NaNNaNQUETZAL CAPITAL PTE. LTD.SingaporeQUETZAL CAPITAL PTE. LTD.0.00.0
61.317979103.843477LAKB2BID1559931SANOFI-SYNTHELABO SINGAPORE PTE LTD5122.0Drugs, Drug Proprietaries, and Druggists' Sundries51220308.0Pharmaceuticals1989.0SubsidiarySANOFI-AVENTIS SINGAPORE PTE. LTD.SingaporePrivateSanofi-Synthelabo Singapore Pte Ltd is primarily engaged in the wholesale distribution of prescription drugs, proprietary drugs, druggists' sundries, and toiletries.NaNActive100.0119.0NaN5.025090e+093.633030e+08Both Imports & ExportsNaNSANOFIFranceSANOFI-AVENTIS SINGAPORE PTE. LTD.0.00.0
71.282887103.850849LAKB2BID679914SOLARIS PARTNERS PTE. LTD.6719.0Offices of Holding Companies, Not Elsewhere Classified67190000.0Holding companies, nec2010.0SubsidiaryGEMINI PARTNERS PTE. LTD.SingaporePrivateSolaris Partners Pte. Ltd. is primarily engaged in holding or owning securities of companies other than banks, for the sole purpose of exercising some degree of control over the activities of the companies whose securities they hold.NaNActive10.04.04.01.026308e+061.026308e+06NaNNaNGEMINI PARTNERS PTE. LTD.SingaporeNaN0.00.0
81.318815103.892581LAKB2BID4688489FMC TECHNOLOGIES GLOBAL SERVICES PTE. LTD.7361.0Employment Agencies73610102.0Labor contractors (employment agency)2013.0SubsidiaryFMC Technologies Global B.V.NetherlandsPrivateFmc Technologies Global Services Pte. Ltd. is primarily engaged in providing employment services, except theatrical employment agencies and motion picture casting bureaus. Establishments classified here may assist either employers or those seeking employment.NaNActive15.015.0NaN6.493420e+056.725700e+09NaNNaNTECHNIPFMC PLCUnited KingdomFMC TECHNOLOGIES GLOBAL SERVICES PTE. LTD.1.00.0
91.282957103.816935LAKB2BID5108278FALCON OILFIELD SERVICES PTE. LTD.6719.0Offices of Holding Companies, Not Elsewhere Classified67190000.0Holding companies, nec2004.0SubsidiaryFALCON ENERGY GROUP LIMITEDSingaporePrivateFalcon Oilfield Services Pte. Ltd. is primarily engaged in holding or owning securities of companies other than banks, for the sole purpose of exercising some degree of control over the activities of the companies whose securities they hold.NaNActiveNaN150.0150.03.424410e+083.424410e+08NaNNaNFALCON ENERGY GROUP LIMITEDSingaporeFALCON ENERGY GROUP LIMITED0.00.0
LATITUDELONGITUDEAccountIDCompanySIC CodeIndustry8-Digit SIC Code8-Digit SIC DescriptionYear FoundEntity TypeParent CompanyParent CountryOwnership TypeCompany DescriptionSquare FootageCompany Status (Active/Inactive)Employees (Single Site)Employees (Domestic Ultimate Total)Employees (Global Ultimate Total)Sales (Domestic Ultimate Total USD)Sales (Global Ultimate Total USD)Import/Export StatusFiscal Year EndGlobal Ultimate CompanyGlobal Ultimate CountryDomestic Ultimate CompanyIs Domestic UltimateIs Global Ultimate
291721.352457103.757745LAKB2BID5317488SALOBO INVESTMENTS PTE. LTD.6719.0Offices of Holding Companies, Not Elsewhere Classified67190000.0Holding companies, nec2019.0ParentSALOBO INVESTMENTS PTE. LTD.SingaporePrivateSalobo Investments Pte. Ltd. is primarily engaged in holding or owning securities of companies other than banks, for the sole purpose of exercising some degree of control over the activities of the companies whose securities they hold.NaNActiveNaN4.04.01026308.01.026308e+06NaNNaNSALOBO INVESTMENTS PTE. LTD.SingaporeSALOBO INVESTMENTS PTE. LTD.1.01.0
291731.332127103.757841LAKB2BID8566146UNIVERSAL LEAF (ASIA) PTE LTD5159.0Farm-Product Raw Materials, Not Elsewhere Classified51590602.0Tobacco, leaf1997.0SubsidiaryUniversal CorporationUnited StatesPrivateUniversal Leaf (Asia) Pte Ltd is primarily engaged in buying and/or marketing farm products, not elsewhere classified.NaNActiveNaN12.025000.0267414.02.569824e+09Both Imports & ExportsNaNUniversal CorporationUnited StatesUNIVERSAL LEAF (ASIA) PTE LTD1.00.0
291741.284247103.851050LAKB2BID9759880INFOTECH HOLDINGS PTE. LTD.6719.0Offices of Holding Companies, Not Elsewhere Classified67190000.0Holding companies, nec2004.0ParentINFOTECH HOLDINGS PTE. LTD.SingaporePrivateInfotech Holdings Pte. Ltd. is primarily engaged in holding or owning securities of companies other than banks, for the sole purpose of exercising some degree of control over the activities of the companies whose securities they hold.NaNActiveNaN4.04.01026308.01.026308e+06NaNNaNINFOTECH HOLDINGS PTE. LTD.SingaporeINFOTECH HOLDINGS PTE. LTD.1.01.0
291751.292221103.850613LAKB2BID4434340BARTER.SG PTE. LTD.7389.0Business Services, Not Elsewhere Classified73890000.0Business services, nec2009.0SubsidiaryINTELLI SOFTWARES PTE. LTD.SingaporePrivateBarter.Sg Pte. Ltd. is primarily engaged in furnishing business services, not elsewhere classified, such as bondspersons, drafting services, lecture bureaus, notaries public, sign painting, speakers' bureaus, water softening services, and auctioneering services, on a commission or fee basis.NaNActive25.010.010.0440460.04.404600e+05NaNNaNINTELLI SOFTWARES PTE. LTD.SingaporeINTELLI SOFTWARES PTE. LTD.0.00.0
291761.277753103.848429LAKB2BID5541092RYB ENGINEERING PTE LTD1731.0Electrical Work17310000.0Electrical work1996.0SubsidiaryCHUDENKO CORPORATIONJapanPrivateRyb Engineering Pte Ltd is a special trade contractor primarily engaged in electrical work at the site.NaNActive100.0100.04556.06344614.01.402050e+09Imports2020-12-31T05:00:00ZCHUDENKO CORPORATIONJapanRYB ENGINEERING PTE LTD1.00.0
291771.355309103.887857LAKB2BID5423564DYSTAR GLOBAL HOLDINGS (SINGAPORE) PTE. LTD.6719.0Offices of Holding Companies, Not Elsewhere Classified67199901.0Investment holding companies, except banks2009.0SubsidiarySENDA INTERNATIONAL CAPITAL LIMITEDHong Kong SARPrivateDystar Global Holdings (Singapore) Pte. Ltd. is primarily engaged in holding or owning securities of companies other than banks, for the sole purpose of exercising some degree of control over the activities of the companies whose securities they hold.NaNActiveNaN50.06615.02949122.02.943975e+09NaN2020-12-31T05:00:00ZZhejiang Longsheng Group Co., Ltd.ChinaDYSTAR GLOBAL HOLDINGS (SINGAPORE) PTE. LTD.1.00.0
291781.319605103.898298LAKB2BID6196188ORTUS HOLDINGS LTD.6719.0Offices of Holding Companies, Not Elsewhere Classified67190000.0Holding companies, necNaNIndependentNaNNaNPrivateOrtus Holdings Ltd. is primarily engaged in holding or owning securities of companies other than banks, for the sole purpose of exercising some degree of control over the activities of the companies whose securities they hold.NaNActiveNaN4.04.01026308.01.026308e+06NaNNaNNaNNaNNaN0.00.0
291791.316363103.924303LAKB2BID6100985ABRDN ASIA LIMITED6726.0Unit Investment Trusts, Face-Amount Certificate offices, and Closed-End Management Investment Offices67269905.0Management investment funds, closed-end1991.0SubsidiaryABRDN HOLDINGS LIMITEDUnited KingdomPublicAbrdn Asia Limited is primarily engaged in issuing unit investment trusts or face-amount certificates; and in issuing shares, other than unit investment trusts and face-amount certificate companies, whose shares contain no provision requiring redemption by the company upon request of the security holder. Unit investment trust companies (1) are organized under a trust indenture, contract of custodianship or agency, or similar instrument; (2) do not have a board of directors; and (3) issue only securities redeemable at the request of the security holder, each of which represents an undivided interest in a unit of specified securities, but does not include voting trusts. Face-amount certificates, sometimes referred to as guaranteed face-amount certificates, are essentially obligations of the issuing company to pay a fixed sum at a specified maturity date and usually require periodic payments by the purchaser.NaNActiveNaN5.0NaN228973073.04.114318e+08Exports2021-12-31T05:00:00ZABRDN HOLDINGS LIMITEDUnited KingdomABRDN ASIA LIMITED1.00.0
291801.295595103.858968LAKB2BID5144338FANSIPAN HOLDINGS PTE. LTD.6719.0Offices of Holding Companies, Not Elsewhere Classified67190000.0Holding companies, nec2018.0SubsidiaryENCYCLIA 1 INVESTMENTS PTE. LTD.SingaporePrivateFansipan Holdings Pte. Ltd. is primarily engaged in holding or owning securities of companies other than banks, for the sole purpose of exercising some degree of control over the activities of the companies whose securities they hold.NaNActive10.04.04.01026308.01.026308e+06NaNNaN65EP INVESTMENT I PTE. LTD.Singapore65EP INVESTMENT I PTE. LTD.0.00.0
291811.311769103.801710LAKB2BID6700434WHOLESOME FOOD PEOPLE PTE. LTD.5099.0Durable Goods, Not Elsewhere Classified50990000.0Durable goods, nec2018.0SubsidiaryTRUSSCO HOLDINGS PTE. LTD.SingaporePrivateWholesome Food People Pte. Ltd. is primarily engaged in the wholesale distribution of durable goods, not elsewhere classified, such as musical instruments and forest products, except lumber.NaNActive11.04.04.01026308.01.026308e+06NaNNaNTRUSSCO HOLDINGS PTE. LTD.SingaporeTRUSSCO HOLDINGS PTE. LTD.0.00.0